Vehicle image sensor cleaning

Abstract

A vehicle computer includes a memory and a processor programmed to execute instructions stored in the memory. The instructions include comparing a captured image of a predetermined object to a target image of the predetermined object to quantify a first noise characteristic of the captured image, comparing the first noise characteristic to a first predetermined threshold, and detecting debris on an image sensor that outputs the captured image as a result of comparing the first noise characteristic to the first predetermined threshold.

The invention claimed is: 
     
       1. A vehicle computer comprising:
 a memory; and 
 a processor programmed to execute instructions stored in the memory, the instructions include comparing a captured image of a predetermined object to a target image of the predetermined object to quantify a first noise characteristic of the captured image, comparing the first noise characteristic to a first predetermined threshold, and detecting debris on an image sensor that outputs the captured image as a result of comparing the first noise characteristic to the first predetermined threshold. 
 
     
     
       2. The vehicle computer of  claim 1 , wherein the first noise characteristic is at least one of a signal-to-noise ratio and a peak signal-to-noise ratio and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the first noise characteristic is below the first predetermined threshold. 
     
     
       3. The vehicle computer of  claim 2 , wherein the instructions include comparing the captured image to the target image to quantify a second noise characteristic of the captured image, wherein the second noise characteristic includes at least one of a root mean squared error and a mean absolute error, and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the second noise characteristic exceeds a second predetermined threshold. 
     
     
       4. The vehicle computer of  claim 3 , wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of the determining that the first noise characteristic is below the first predetermined threshold and the second noise characteristic exceeds the second predetermined threshold. 
     
     
       5. The vehicle computer of  claim 1 , wherein the instructions include initiating cleaning of the image sensor as a result of detecting debris on the image sensor. 
     
     
       6. The vehicle computer of  claim 5 , wherein initiating cleaning of the image sensor includes outputting a control signal to a sensor cleaning system. 
     
     
       7. The vehicle computer of  claim 1 , wherein the instructions include identifying the predetermined object in an original image captured by the image sensor. 
     
     
       8. The vehicle computer of  claim 1 , wherein the instructions include generating the captured image by manipulating the original image captured by the image sensor. 
     
     
       9. The vehicle computer of  claim 8 , wherein manipulating the original image includes at least one of cropping the original image and normalizing the original image. 
     
     
       10. The vehicle computer of  claim 9 , wherein normalizing the original image includes adjusting at least one of an exposure, a brightness, and an orientation of the predetermined object in the original image. 
     
     
       11. The vehicle computer of  claim 9 , wherein cropping the original image includes removing sections of the original image that do not represent the predetermined object. 
     
     
       12. A method comprising:
 comparing a captured image of a predetermined object to a target image of the predetermined object to quantify a first noise characteristic of the captured image; 
 comparing the first noise characteristic to a first predetermined threshold; and 
 detecting debris on an image sensor that outputs the captured image as a result of comparing the first noise characteristic to the first predetermined threshold. 
 
     
     
       13. The method of  claim 12 , wherein the first noise characteristic is at least one of a signal-to-noise ratio and a peak signal-to-noise ratio and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the first noise characteristic is below the first predetermined threshold. 
     
     
       14. The method of  claim 13 , further comprising comparing the captured image to the target image to quantify a second noise characteristic of the captured image, wherein the second noise characteristic includes at least one of a root mean squared error and a mean absolute error, and wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of determining that the second noise characteristic exceeds a second predetermined threshold. 
     
     
       15. The method of  claim 14 , wherein detecting debris on the image sensor includes detecting debris on the image sensor as a result of the determining that the first noise characteristic is below the first predetermined threshold and the second noise characteristic exceeds the second predetermined threshold. 
     
     
       16. The method of  claim 12 , further comprising initiating cleaning of the image sensor as a result of detecting debris on the image sensor. 
     
     
       17. The method of  claim 12 , further comprising identifying the predetermined object in an original image captured by the image sensor. 
     
     
       18. The method of  claim 12 , further comprising generating the captured image by manipulating the original image captured by the image sensor, wherein manipulating the original image includes at least one of cropping the original image and normalizing the original image. 
     
     
       19. The method of  claim 18 , wherein normalizing the original image includes adjusting at least one of an exposure, a brightness, and an orientation of the predetermined object in the original image. 
     
     
       20. The method of  claim 18 , wherein cropping the original image includes removing sections of the original image that do not represent the predetermined object.